AI for business analysts: How the role is changing

AI is shifting business analysts’ work away from repetitive reporting, routine data pulls, dashboard scans, and basic query changes toward higher-value activities such as investigating unusual results, applying business context, governing metrics, and advising stakeholders. The article argues that analyst teams face structural capacity limits because data requests grow faster than hiring, while recurring requests can crowd out novel analysis. AI tools and warehouse-native models can draft reports, answer governed natural-language questions, and identify anomalies for review, but analysts remain responsible for validating outputs, tracing answers to source data, framing precise questions, and recognizing organizational context that models may miss. As self-service analytics expands, analysts increasingly build and maintain the certified metrics, trusted models, definitions, documentation, and data lineage that enable reliable access for business users. Sigma is presented as a platform supporting this model through governed AI-assisted querying, inspectable workbook-based analysis, embedded self-service capabilities, and configurable agents for automating recurring workflows across cloud data warehouses.

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